Field
The present invention relates to a system and method for an autonomous garden tool. Such tool may be a lawn mower. The system and method of the invention are particularly suited for generating an HDR image on the basis of two images out of a sequence of images captured by a camera of the autonomous garden tool.
Description of the Related Art
Technical developments often are intended to increase the comfort of use for the user. Since many people are bothered by gardening work that has to be performed regularly, e.g. lawn mowing, autonomous tools have been developed. With these autonomous garden tools it is no longer necessary for a person to be present when the lawn is mowed. Such lawn mowers have a motor for propelling the lawn mower and furthermore there are detection systems provided in order to avoid that the lawn mower drives through an area where lawn mowing is not needed or wanted. Such areas may be any obstacles that are present on the lawn or may be defined by the edge of an area like the borderline to a terrace. Such edges in the past were marked by an electric border wire which reliably limited the area of movement of the autonomous lawn mower.
For avoiding contact with obstacles that cannot be indicated by such a border wire the autonomous garden tool usually has additional sensors like a bump-sensor and/or a sonar-sensor. But still there is an interest in improving the detection capabilities of small obstacles which may lie on the grass. In particular the bump-sensors are only suitable for obstacles with a minimum height so that the autonomous lawn mower touches the obstacle with its bump-sensor before it turns away and changes the direction of movement. As it can be easily gathered from such a situation it would be preferred if contact with the obstacle can be avoided completely and in particular if the detection of such obstacles could be improved so that a flat item like for example a cellular phone lying in the grass may be detected reliably.
A further known development is therefore to the use of a camera and detection of objects by image processing. Such a system comprising a camera and used in an autonomous lawn mower is described in EP 2 620 050 A1. For adapting the system to different lighting conditions it is suggested in this publication to adapt the setting of the camera. By doing so it is possible to use the system even if lighting conditions are difficult. To further improve it is suggested to use an additional light source that may be switched on if the environment becomes too dark for performing a serious evaluation of a captured image of the camera. Such an adaptation of the camera setting with respect to exposure time and gain can be performed in a time series manner. But there are strong limitations of such system because an image captured by a camera may include dark areas as well as bright areas. Such a situation may for example occur if the lawn mower enters an area where shades of trees in bright sunlight are included in a captured image. The reason is that the dynamic range (intraframe) of a camera sensor typically is limited (about 60 db). Such problem may be solved by using a so-called bracketing technique in which two images taken with different camera settings are combined in order to generate an HDR image.
When HDR images are used for further image processing it has to be ensured that the quality of the HDR image itself is high. There is no sense in generating a HDR image that is improved with respect to the contrast of the image but contains artifacts because of the HDR image generating process. Thus, using the bracketing technique, the time difference between image frames from which the HDR image is calculated should be as short as possible. Otherwise the images that form the basis of the HDR image do not show exactly the same scene. This happens when there is a moving object for example or also when the camera moves.
The use of a FPGA system merging three images captured with different settings is described for robotic applications in “High Dynamic Range Real-Time Vision Systems for Robotic Applications” by Lapray, Heyrman, Rosse and Ginhac.
The problem of such an approach is that the consumer market which is the main market for such autonomous garden tools is very cost-sensitive. Using camera sensors that have the capability of quickly adapting to new camera settings are rather expensive and thus the entire costs for such an autonomous garden tool would increase. And with cameras that apply changed camera settings slower it is not known which image in a sequence of images was captured with which setting. In order to use a low-cost camera sensor having no HDR-functionality, nevertheless, it is suggested in EP 2 620 050 A1 to stop the autonomous lawn mower until two images with different settings are captured. In situations where the contrast changes often while the autonomous garden tool is use this will lead to a significant increase in the time until an area is completely worked.